For the second scenario, we validate the identity of every tenth frame of the recorded video sessions using five frames per identity as a reference set. We report these results in Table REF . In addition to the recognition accuracy at different K, we also report the identity ranking: the index of the true face's facial feature distance within the reference dataset, as reported by [1]}. To compare our results with existing benchmarks, we also report the mean index of the original and DeepFakeshttps://github.com/deepfakes/faceswap stimuli contained within the FaceForensics++ dataset [2]}, processing ten uniformly spaced frames from each video.
